NA Digest, V. 21, # 38
NA Digest Tuesday, October 12, 2021 Volume 21 : Issue 38
Today's Editor:
Daniel M. Dunlavy
Sandia National Labs
dmdunla@sandia.gov
Today's Topics:
- Anymatrix MATLAB toolbox, version 1.0
- MPLAPACK version 1.0.0 released
- New release, preCICE v2.3
- Householder Symposium XXI, Jun 2022
- Senior Research Scientist Position, Scientific Computing, Simula
- Professor Position, Hertz Chair, Univ of Bonn
- Faculty Position, Comp Medicine and Math, UNC-Chapel Hill
- Faculty Position, Computing and Mathematical Sciences, Caltech
- Faculty Position, Data Science, IISER Pune, India
- Tenure Track Position, Applied and Comp Math, Florida State Univ
- Hooke Fellowship Positions, Oxford
- Wilkinson Fellowship Position, Scientific Computing, Argonne
- Postdoc Position, Battery Simulation, KIT
- Postdoc Position, Exascale Computing
- Postdoc Position, Florida State Univ
- Postdoc Position, ML/Digital Twins, Oden Institute, UT Austin
- Postdoc Position, Neural Network Training, Sandia NL
- Postdoc Position, Scientific ML, Sandia National Laboratories
- Postdoc Positions, Sci Comp/Stats/Imaging/ML, CCM, Flatiron Inst
- PhD Position, Comp Science and Engineering, Umea Univ
- PhD Position, Numerical Analysis and Simulation, HKU
- PhD Positions, Numerical Analysis, Univ of Bologna, Italy
- Contents, Electronic Transactions on NA (ETNA), 54
- Contents, Iranian J of Numerical Analysis and Optimization, 11 (2)
- Contents, Numerical Algorithms, 88 (3)
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From: Nick Higham nick.higham@manchester.ac.uk
Date: October 11, 2021
Subject: Anymatrix MATLAB toolbox, version 1.0
We have just released version 1.0 of Anymatrix, a MATLAB toolbox that
provides an extensible collection of matrices, organized in groups,
with the ability to search the collection by matrix properties.
Notable features include:
- a large collection of Hadamard matrices
- real-life matrices from networks
- matrices built-in to MATLAB (including gallery) can be searched by
property
For the software and documentation see
https://github.com/mmikaitis/anymatrix
Nick Higham and Mantas Mikaitis
From: NAKATA Maho maho.nakata@gmail.com
Date: October 09, 2021
Subject: MPLAPACK version 1.0.0 released
The MPLAPACK (formerly MPACK) is a multiple-precision version of
LAPACK (https://www.netlib.org/lapack/) MPLAPACK version 1.0.0 is
based on the LAPACK version 3.9.1 and translated from Fortran 90 to
C++ using FABLE, a Fortran to C++ source-to-source conversion tool
(https://github.com/cctbx/cctbx_project/tree/master/fable). MPLAPACK
version 1.0.0 provides the real and complex version of MPBLAS, and the
real version of MPLAPACK supports all LAPACK features: solvers for
systems of simultaneous linear equations, least-squares solutions of
linear systems of equations, eigenvalue problems, and singular value
problems, and related matrix factorizations except for rectangular
complete packed matrix form and mixed-precision routines. Besides,
MPLAPACK supports a part of the complex routines of LAPACK, such as
diagonalization of Hermite matrices, Cholesky factorization, and
matrix inversion. The MPLAPACK defines an API for numerical linear
algebra, similar to LAPACK. It is easy to port legacy C/C++ numerical
codes using MPLAPACK. MPLAPACK supports binary64, binary128, FP80
(extended double), MPFR, GMP, and QD libraries (double-double and
quad-double). Users can choose MPFR or GMP for arbitrary accurate
calculations, double-double or quad-double for fast 32 or 64 decimal
calculations. We can consider the binary64 version as the C++ version
of LAPACK. MPLAPACK is available at GitHub
(https://github.com/nakatamaho/mplapack) under the 2-clause BSD
license.
From: Benjamin Uekermann benjamin.uekermann@ipvs.uni-stuttgart.de
Date: October 07, 2021
Subject: New release, preCICE v2.3
A new preCICE release, v2.3, is just out. The new version comes with
much improved memory footprint of mesh data structures, better
capabilities to couple many solvers fully implicitly, and many
usability improvements. More information:
https://precice.discourse.group/t/highlights-of-the-new-precice-release-v2-3/750
What is preCICE?
https://www.precice.org/
preCICE is a coupling library for partitioned multi-physics
simulations, including, but not restricted to fluid-structure
interaction and conjugate heat transfer simulations. The software
offers methods for transient equation coupling, communication, and
data mapping. preCICE is written in C++ and offers additional bindings
for C, Fortran, Matlab, and Python. Ready-to-use adapters for many
solvers, such as OpenFOAM, deal.II, FEniCS, SU2, or CalculiX, are
available. Due to the minimally-invasive approach of preCICE, adapters
for in-house codes can be implemented and validated in only a few
weeks. preCICE is an open-source software under the LGPL3 license.
From: Heike Fa=C3=9Fbender h.fassbender@tu-braunschweig.de
Date: October 07, 2021
Subject: Householder Symposium XXI, Jun 2022
The Householder Symposium XXI on Numerical Linear Algebra has been
rescheduled to be held at Hotel Sierra Silvana, Selva di Fasano (Br),
Italy, 12-17 June 2022.
The Symposium is very informal, with the intermingling of young and
established researchers a priority. Attendance is by invitation
only. Each attendee will be given the opportunity to present a talk or
a poster. Some talks will be plenary lectures, while others will be
shorter presentations arranged in parallel sessions. Participants are
expected to attend the entire meeting. Anyone accepted for HHXI in
2020 has a valid invitation for 2022. In February 2022, we will
re-open the application process to fill any vacancies that arise due
to cancellations as a result of the new situation. Applications will
be solicited from researchers in numerical linear algebra, matrix
theory, and related areas such as optimization, differential
equations, signal processing, control, and data science.
From: Marie E Rognes meg@simula.no
Date: October 06, 2021
Subject: Senior Research Scientist Position, Scientific Computing, Simula
Simula Research Laboratory invites applications for one Senior
Research Scientist position in the field of Scientific
Computing. Scientific Computing at Simula focuses on fundamental
research of an interdisciplinary nature targeting important problems
in science and society. Applicants are expected to develop and sustain
a research program extending or complementing our core research areas:
scientific computing, modelling and simulation, high-performance
computing, numerical analysis, data science and computational science,
computational mechanics, computational life science including
computational cardiovascular modelling and computational neuroscience.
For information about the position, application requirements and how
to apply, see:
https://www.simula.no/about/job/call-senior-research-scientist-scientific-computing-simula-research-laboratory
The position is permanent, and the workplace will be at Simula's
premises in Oslo, Norway. Application deadline: Nov 1 2021.
From: J=C3=BCrgen D=C3=B6lz doelz@ins.uni-bonn.de
Date: October 04, 2021
Subject: Professor Position, Hertz Chair, Univ of Bonn
The University of Bonn calls for applications for a Hertz Chair (W3,
full professorship) at the interface of Mathematics, Modelling and
Simulation of Complex Systems starting as soon as possible.
Establishing distinguished Hertz Chairs at the interface of
outstanding research areas at the University of Bonn is a central
measure following the success of the University of Bonn within the
German Excellence Strategy, a funding program of the Federal and State
Governments to support cutting-edge research at universities. Under
this scheme, the University of Bonn establishes an exceptionally
endowed Hertz Chair within the Transdisciplinary Research Area (TRA)
"Mathematics, Modelling and Simulation of Complex Systems".
For more information please consider
https://www.uni-bonn.de/de/universitaet/medien-universitaet/medien-organisation-und-einrichtungen/medien-dezernat-3/w3-hertz-chair-mathematics-modelling-simulation-of-complex-systems.pdf
From: Boyce Griffith boyceg@email.unc.edu
Date: October 06, 2021
Subject: Faculty Position, Comp Medicine and Math, UNC-Chapel Hill
The Computational Medicine Program in the School of Medicine and the
Department of Mathematics in the College of Arts and Sciences at the
University of North Carolina at Chapel Hill (UNC-CH) invite applicants
for a tenure-track faculty position. The Computational Medicine
Program is a recently established research initiative that seeks to
apply modern computational approaches, including mathematical and
statistical modeling, machine learning, and network analysis, to
problems relevant to human health and disease. Candidates who aim to
establish a research program in any area of mathematics with
applications to understanding mechanisms of human diseases and the
goal of impacting diagnosis and treatment are strongly encouraged to
apply. A Ph.D. or equivalent degree is required, and postdoctoral
experience, outstanding research promise, and dedication to excellent
teaching are expected. Appointments are expected to be made at the
level of assistant professor, but exceptionally well qualified
candidates of higher rank will also be considered. This position
includes an affiliation and research space within the Computational
Medicine Program at UNC School of Medicine and a full- time faculty
appointment within the Department of Mathematics in the College of
Arts and Sciences. The successful candidate will be expected to direct
an independent research program supported by extramural funding and to
participate in team science projects initiated through the
Computational Medicine Program. Duties of this position will also
include student mentoring and teaching at the undergraduate and
graduate level through the Department of Mathematics. An excellent
start-up package and access to departmental and institutional
facilities will be provided, including access to outstanding
computational resources (https://its.unc.edu/research-computing).
Applicants must apply online at
https://unc.peopleadmin.com/postings/200417. In addition to
information requested by the UNC website, applicants should post the
following at https://www.mathjobs.org/jobs/list/18500: (1) the
standard AMS cover sheet; (2) curriculum vitae; (3) a description of
current research and a plan for future research; (4) a statement of
teaching goals; and (5) at least four letters of recommendation. Note
that candidates must apply at the UNC website as well as at
MathJobs.org to be considered for the position.
Review of applications will begin on November 1, 2021 and will
continue until the position is filled. The anticipated position start
date is July 1, 2022. For further information on the Program or
Department, please visit https://www.med.unc.edu/compmed and
https://math.unc.edu, or contact Tim Elston or Boyce Griffith at
timothy_elston@med.unc.edu or boyceg@email.unc.edu.
From: Sydney Garstang sydney@caltech.edu
Date: October 11, 2021
Subject: Faculty Position, Computing and Mathematical Sciences, Caltech
The Computing and Mathematical Sciences (CMS) Department at the
California Institute of Technology (Caltech) invites applications for
tenure- track faculty appointments. Exceptional applications at the
tenured level may also be considered. The CMS Department is part of
the Division of Engineering and Applied Science (EAS), comprising
researchers working in and between the fields of aerospace, civil,
electrical, environmental, mechanical, and medical engineering, as
well as materials science and applied physics. The Institute as a
whole represents the full range of research in biology, chemistry,
engineering, geological and planetary sciences, physics, and the
social sciences. We welcome applicants with research and teaching
interests in any area of computer science and/or applied mathematics,
broadly defined, including research that connects to other fields at
Caltech. Commitments to world- class research, to high-quality
teaching and mentoring, and to enhancing diversity, equity, and
inclusivity are expected. Appointment as an assistant professor is
contingent upon the completion of a Ph.D. degree in computer science,
applied mathematics or related areas. An initial appointment at the
assistant professor level is four years. Reappointment beyond the
initial term is contingent upon successful review conducted prior to
the commencement of the fourth year. Applications will be reviewed
beginning 25 October 2021, and all applications completed with all
required materials uploaded before 1 December 2021 will receive full
consideration. For a list of all documents required, and full
instructions on how to apply online, please visit
https://applications.caltech.edu/jobs/cms. Questions about the
application process may be directed to search@cms.caltech.edu.
Caltech has implemented a mandatory vaccination policy effective
October 15, 2021, requiring COVID-19 vaccinations for all employees
(with Institute-approved exemptions for religious or medical
contraindications only). At present, an individual is deemed "fully
vaccinated" when that person has received, at least 14 days prior,
either the second dose in a two-dose COVID-19 vaccine series (e.g.,
Pfizer or Moderna) or a single- dose COVID-19 vaccine (e.g., Johnson &
Johnson). As a condition of employment, employees must submit official
COVID-19 vaccine documentation. More information may be found at
https://together.caltech.edu.
From: Amit Apte a.s.apte@gmail.com
Date: October 07, 2021
Subject: Faculty Position, Data Science, IISER Pune, India
The Department of Data Science at the Indian Institute of Science
Education and Research (IISER) Pune invites applications from
candidates with outstanding academic records in foundations and
applications of data science for faculty positions at the level of
Assistant Professor, Associate Professor, and Professor.
The department carries out research on mathematical and theoretical
aspects of data science and development of new methods. Building on
the existing core strengths of IISER Pune in basic sciences and
humanities, the faculty collaborate on a variety of applications of
data science. We are actively seeking candidates in the areas of
artificial intelligence & machine learning, optimisation, statistical
methods & theory, across the disciplines of computer science, applied
mathematics, and statistics.
IISER Pune faculty get a generous start-up grant. They also lead
active research groups and secure extra-mural funding. Collaborations
with industry and academia, especially with other faculty at IISER
Pune, are highly encouraged.
At IISER Pune, some of the best practitioners of science train India's
brightest young minds as part of its flagship BS-MS, Integrated PhD,
and PhD programs. Faculty members are expected to teach courses
related to data science at the undergraduate and graduate
level. Further information is available .
Detailed educational qualifications for each level and instructions
for applying are at . Priority consideration will be given to
applications received by 15 December 2021.
From: Sanghyun Lee lee@math.fsu.edu
Date: October 04, 2021
Subject: Tenure Track Position, Applied and Comp Math, Florida State Univ
Applications are invited for a tenure-track Assistant Professor
position in applied and computational mathematics at Florida State
University, with a start date of August 2022. Candidates should have a
doctoral degree from an accredited institution in mathematics or a
related discipline with a demonstrated record of achievement in
teaching, academic research, and service. Postdoctoral experience in
some area of applied mathematics is required. The ideal candidate will
have experience working in one or several research areas that
complement the existing research focus of the mathematics
department. This includes applied and geometric partial differential
equations; computational mathematics in its broadest sense;
optimization algorithms; and data science and machine learning.
Florida State University is one of two flagship research universities
in the State University System of Florida, and is ranked number 19
among all public universities in the country by U.S. News and World
Report. The university enrolls over 40,000 students in the main
campus of Tallahassee. Tallahassee is located in north Florida and has
a population of roughly 190,000. It is adjacent to the Apalachicola
National Forest and about twenty-five miles from the Gulf of Mexico,
with easy access to pristine beaches and other natural
habitats. Tallahassee has a warm climate, with an annual average high
temperature of 80 degrees Fahrenheit and an annual average low
temperature of 56 degrees Fahrenheit.
Apply via http://jobs.fsu.edu/ to Job opening ID 49971, as well as
through MathJobs.org. Submit a cover letter, curriculum vitae, and
research and teaching statements electronically to Mathjobs.org and to
the FSU job site http://jobs.fsu.edu/. Additionally, four letters of
recommendation (at least one of the letters should address the
candidate's teaching capability) must be submitted to MathJobs.org.
The deadline to apply for this position is November 1,
2021. Candidates from underrepresented groups are encouraged to apply.
From: Nick Trefethen trefethen@maths.ox.ac.uk
Date: October 08, 2021
Subject: Hooke Fellowship Positions, Oxford
Oxford will be appointing several new Hooke Fellows this year. This
is a high-prestige three-year position in numerical analysis, data
science, or other areas of applied mathematics -- please see
https://www.maths.ox.ac.uk/node/39999 for details. The closing date
for applications is November 3.
From: Emil Constantinescu emconsta@mcs.anl.gov
Date: October 08, 2021
Subject: Wilkinson Fellowship Position, Scientific Computing, Argonne
The Mathematics and Computer Science Division of Argonne National
Laboratory invites outstanding candidates to apply for the 2022 J.H.
Wilkinson Postdoctoral Fellowship in Scientific Computing. The
Wilkinson Fellowship is intended to encourage early-career scientists
actively engaged in state-of-the-art research in scientific
computing. The fellowship provides an exceptional opportunity for
innovative research in computational mathematics and scientific
computing on advanced computing architectures.
Areas of interest span the applied mathematics, scientific computing
and computational sciences and include algorithmic differentiation,
computational fluid dynamics, data assimilation, data science,
discretization, linear algebra, machine learning, meshing, modeling
and simulation, solvers, multifidelity/ multilevel/ multiphysics/
multiscale algorithms, quantum computing, operations research,
optimization, statistics, stochastic systems, and uncertainty
quantification. Additional areas of interest in applied mathematics,
numerical software, and statistics can be found at
https://www.anl.gov/mcs/lans .
We value and strive for diversity in backgrounds, experiences, and
perspectives. The appointment is for one year and may be renewed for
another year. For full consideration, applications and letters should
be submitted by December 1, 2021. For more details and to apply, see
https://www.anl.gov/mcs/wilkinson .
From: Willy D=C3=B6rfler willy.doerfler@kit.edu
Date: October 07, 2021
Subject: Postdoc Position, Battery Simulation, KIT
Our project concerns research in the area of models and numerical
simulation of Lithium-Ion Batteries at the particle level or cell
level. Especially, we aim at development and application of
data-driven methods (data-driven computational mechanics or neural
networks). The project and position is located at the Institute of
Numerical and Applied Mathematics are part of the research training
group "Simulation of Mechano-Electro-Thermal Processes in
Lithium-Ion-Batteries" at KIT. More information on
https://www.pse.kit.edu/karriere/joboffer.php?id=3D20447&new=3Dtrue&language=3Den
From: Laura Cornell ads@adclub.com
Date: October 06, 2021
Subject: Postdoc Position, Exascale Computing
Exascale Computing Postdoctoral Fellow - 93950
Organization: NE-NERSC
Lawrence Berkeley National Lab's (LBNL, https://www.lbl.gov/) NERSC
Division (https://www.nersc.gov/about/) has an opening for an Exascale
Computing Postdoctoral Fellow to join the team. The National Energy
Research Scientific Computing Center (NERSC) at Lawrence Berkeley
National Laboratory seeks a highly motivated postdoc to join the NERSC
efforts to ensure math libraries perform well on upcoming
computational platforms. The postdoc will collaborate with selected
Exascale Computing Project (ECP) math libraries and scientific
application teams to enable the solution of deep, meaningful problems
targeted by the ECP program as well as other program areas funded by
the Department of Energy Office of Science
(https://www.energy.gov/science/office-science).
What You Will Do: Work with NERSC staff and code teams to transition
and optimize math libraries for ECP applications and selected non-ECP
applications important to the NERSC workload for the Perlmutter system
as well as the upcoming OLCF Frontier and ALCF Aurora systems in
performance- portable ways. Conduct profiling and scaling studies as
well as parallelization, memory bandwidth for these codes.
Disseminate results of research activities through refereed
publications, reports, and conference presentations. Ensure that new
methods are documented for the broader community, NERSC staff,
vendors, and NERSC users. Participation in postdoctoral career and
science enrichment activities within the Berkeley Lab Computing
Sciences Area is encouraged. Occasional to travel to sites at other
labs, universities, and to vendor facilities.
Apply directly online at http://50.73.55.13/counter.php?id=3D209419 and
follow the on-line instructions to complete the application process.
From: Sanghyun Lee lee@math.fsu.edu
Date: October 04, 2021
Subject: Postdoc Position, Florida State Univ
The Department of Mathematics at Florida State University is accepting
applications for full-time postdoctoral positions in Mathematics, with
start dates of August 2022. The appointment is for a period of two
years. Candidates must have a doctoral degree in Mathematics or a
closely related discipline conferred within the last 5 years, a strong
research record, and a commitment to excellence in
teaching. Preference will be given to candidates whose research
interests overlap significantly with those of current faculty
members. Applicants are strongly encouraged to include in their cover
letter the name(s) of FSU faculty whose research best aligns with
their own. Information about the department is available at
www.math.fsu.edu Qualified candidates must apply through both the
MathJobs website (MathJobs.org) and the FSU Employment and Recruitment
Services website at www.jobs.fsu.edu, job opening 50055. Each
applicant must submit a cover letter, a standard AMS coversheet, a
current curriculum vitae, a research statement, and a teaching
statement. Candidates should also arrange to have four letters of
recommendation (one should address the candidate's teaching
qualifications) uploaded directly by the letter writers through the
MathJobs website. The deadline for applications is November 15, 2021,
but early application is advised.
Florida State University is one of two flagship research universities
in the State University System of Florida, with over 40,000 students
in the main campus of Tallahassee. Tallahassee is located in North
Florida and has a population of approximately 190,000. It is adjacent
to the Apalachicola National Forest and about twenty five miles from
the Gulf of Mexico, with easy access to pristine beaches and other
natural habitats. Tallahassee has a warm climate, with an annual
average high temperature of 80 degrees Fahrenheit and an annual
average low temperature of 56 degrees Fahrenheit. Florida State
University is an Equal Opportunity/Access/Affirmative Action/Pro
Disabled & Veteran Employer. FSU's Equal Opportunity Statement can be
accessed at:
https://hr.fsu.edu/sites/g/files/upcbnu2186/files/PDF/Publications/diversity/EEO_Statement.pdf
From: Tan Bui tanbui@oden.utexas.edu
Date: October 05, 2021
Subject: Postdoc Position, ML/Digital Twins, Oden Institute, UT Austin
A postdoc position is immediately available in Tan Bui-Thanh's
research group on Machine Learning for Digital Twin (DT).
Responsibility: Develop model-constrained machine learning approaches
engineering and science applications that are governed by Partial
differential Equations (or their discretizations). Develop algorithms
for monitoring and quantifying uncertainty for DT.
Qualifications: PhD research was in the field of inverse problems
and/or uncertainty quantification and/or machine learning methods. -
Strong in applied mathematics and computation.
Duration: The position can be renewed annually, up to three years.
Please contact Tan Bui-Thanh at tanbui@oden.utexas.edu for
questions/concerns about the position.
From: Eric Cyr eccyr@sandia.gov
Date: October 07, 2021
Subject: Postdoc Position, Neural Network Training, Sandia NL
We are seeking a postdoctoral appointee at the Computer Science
Research Institute with a strong background in the development of
numerical methods focusing on large-scale simulation of partial
differential equations or optimal control problems. The successful
candidate will contribute to an effort developing new machine learning
architectures and training algorithms on leadership class HPC
platforms. This work is targeting applications in scientific machine
learning, where the appointee will work in a team of rearchers to
apply their HPC machine learning technologies to problems of broad
interest to the science and engineering community, including
applications in climate science and plasma physics.
Required Qualifications: PhD in mathematics, computer science, or
related engineering or science field (conferred within 3 years prior
to employment). Experience in numerical methods development for
distributed computing, including one or more of multigrid methods,
parallel-in-time, domain decomposition, hierarchical matrices, or
matrix sketching. Familiarity with optimization or deep learning.
Experience with high-performance parallel computing environments
including MPI, OpenMP or CUDA. Excellent programming and algorithm
development skills as evidenced by software developed by the
applicant. A background that includes research experience evidenced
by a record of research publications and presentations.
To Apply:
1. go to http://www.sandia.gov/careers/studens_postdocs/postdocs.html
2. click 'View All Sandia Openings'
3. search for Job ID: 678691
From: Eric Cyr eccyr@sandia.gov
Date: October 07, 2021
Subject: Postdoc Position, Scientific ML, Sandia National Laboratories
We are seeking a postdoctoral appointee at the Computer Science
Research Institute with a strong background in the development of
numerical methods, and/or development of algorithms for HPC platforms.
The successful candidate will contribute to an effort developing
numerical methods for machine learning on leadership class HPC
platforms. This work is targeting applications in scientific machine
learning, where the appointee will work in a team of researchers to
apply their HPC machine learning technologies to problems of broad
interest to the science and engineering community, including
applications in climate science and plasma physics.
Required qualifications PhD in mathematics, computer science, or
related engineering or science field (conferred within 3 years prior
to employment). Experience in numerical methods development or
developing methods suitable for HPC environments. Experience with
high-performance parallel computing environments including MPI, OpenMP
or CUDA. Excellent programming and algorithm development skills as
evidenced by software developed by the applicant. A background that
includes research experience evidenced by a record of research
publications and presentations. Able to acquire and maintain a DOE
security clearance, which requires US citizenship.
To Apply:
1. go to http://www.sandia.gov/careers/studens_postdocs/postdocs.html
2. click 'View All Sandia Openings'
3. search for Job ID: 678692
From: Alex Barnett abarnett@flatironinstitute.org
Date: October 04, 2021
Subject: Postdoc Positions, Sci Comp/Stats/Imaging/ML, CCM, Flatiron Inst
We are excited to offer several postdoctoral positions at the Center
for Computational Mathematics at the Flatiron Institute, in New York
City. These Flatiron Research Fellows (FRFs) are typically 3-year
academic- style positions, starting in Fall 2022. Our active areas of
research are: numerical analysis and partial differential equations;
high performance computing and software libraries; signal and image
processing, with a particular focus on cryo-electron microscopy;
computational physics, chemistry and biology (statistical mechanics,
biophysics, fluid mechanics, and molecular dynamics); ML for
scientific applications; probabilistic and differential programming;
statistical methodology, modeling, and inference; and mathematics,
algorithms, and optimization for deep neural networks. For current CCM
staff and their interests, see:
https://www.simonsfoundation.org/flatiron/center-for-computational-
mathematics/about/people
While many of our FRFs have an applied/computational mathematics
background, we also seek computational applicants with PhDs from other
science areas. CCM provides an attractive combination of an
academic-style research environment with a lab-style long term view on
tool building and software, plus strong interactions with the four
other centers at the Institute (computational biology, astrophysics,
quantum physics, and neuroscience), as well as area universities.
The application (including a research statement and three letters of
recommendation) is due by December 15, 2021. To see the full ad, and
to apply:
https://simonsfoundation.wd1.myworkdayjobs.com/en-US/ccmcareers/job/162-Fifth-Avenue/Flatiron-Research-Fellow--Machine-Learning-and-Computational-Statistics--CCM_R0000701
From: Siyang Wang siyang.wang@umu.se
Date: October 04, 2021
Subject: PhD Position, Comp Science and Engineering, Umea Univ
The Computational Mathematics research group at Umea University in
Sweden is inviting applications for a PhD position in computational
science and engineering. The aim of the PhD project is to develop
computationally efficient and geometrically flexible numerical
techniques for solving wave propagation problems governed by
hyperbolic partial differential equations. The project focuses both on
the numerical analysis aspect (stability and error estimates) and
efficient implementation (realistic 3D models in the geosciences).
Umea offers excellent working and living conditions. The working
environment is international and very family friendly, as exemplified
by a generous allotment of 480 days paid parental leave for each
child. Umea is a young city located right next to a large river. It is
surrounded by forests and lakes and lies close to the sea. The city
offers excellent opportunities for both outdoor and indoor activities.
For a detailed project description and application procedure, see
https://www.umu.se/en/work-with-us/open-positions/phd-position-in-computational-methods-for-wave-phenomena_433142/
From: Guanglian Li lotusli0707@gmail.com
Date: October 06, 2021
Subject: PhD Position, Numerical Analysis and Simulation, HKU
I am currently recruiting one 4-year PhD candidate based at Department
of Mathematics, The University of Hong Kong. Fields of interest:
Scientific computing and analysis, e.g., Finite Element methods (FEM),
multiscale methods and analysis and high-dimension
approximation. Detailed information can be found here:
https://sites.google.com/d/1QGNbKCOB5-
BOCsQPAhyYQfEOi7Av3Ste/p/12PNOQNMzut13ae_Lv9BbIWZ8ej24WRvd/edit
Please contact Dr. Guanglian Li via lotusli@maths.hku.hk if you are
interested.
From: Margherita Porcelli, Fabiana Zama margherita.porcelli@unibo.it
Date: October 06, 2021
Subject: PhD Positions, Numerical Analysis, Univ of Bologna, Italy
The Department of Mathematics of the University of Bologna has opened
two 3-year PhD student positions - Bando PON "Ricerca e Innovazione"
2014 - 2020 in Numerical Analysis starting next January 2022:
"Mathematical models and numerical methods for environmental
applications of Fast Field Cycling Nuclear Magnetic Resonance"
Advisor: Fabiana Zama
"Black-Box optimization for clean energy technologies"
Advisor: Margherita Porcelli
Applicants must hold a Second Cycle Degree by Oct 31, 2021.
The application deadline is Oct 20, 2021 at 11:59 PM.
Further details can be found here:
https://www.unibo.it/en/teaching/phd/new-call-for-applications-for-phd-additional-scholarships-on-innovation-and-green-topics%2C-funded-by-FSE-REACT-EU---PON-ricerca-e-Innovazione-programme
and
https://www.unibo.it/en/teaching/phd/2021-2022-pon-scholarships-call/mathematics
From: Lothar Reichel reichel@math.kent.edu
Date: October 06, 2021
Subject: Contents, Electronic Transactions on NA (ETNA), 54
L. Grubisic, M. Ljulj, V. Mehrmann, and Josip Tambaca, Modeling and
discretization methods for the numerical simulation of elastic frame
structures.
C. Echeverria, J. Liesen, and P. Tichy, Analysis of the multiplicative
Schwarz method for matrices with a special block structure.
K. Kahl and B. Lang, Hypergraph edge elimination - A symbolic phase
for Hermitian eigensolvers based on rank-1 modifications.
P. Benner and D. Palitta, On the solution of the nonsymmetric
T-Riccati equation.
J. Pablo Lucero Lorca and G. Kanschat, Multilevel Schwarz
preconditioners for singularly perturbed symmetric reaction-diffusion
systems.
F. Fairag, K. Chen, and S. Ahmad, Analysis of the CCFD method for
MC-based image denoising problems.
Sk. Safique Ahmad, I. Ali, and I. Slapnicar, Perturbation analysis of
matrices over a quaternion division algebra.
S. Erfani, E. Babolian, and S. Javadi, New fractional pseudospectral
methods with accurate convergence rates for fractional differential
equations.
J. Park, Pseudo-linear convergence of an additive Schwarz method for
dual total variation minimization.
S. Franz, Continuous time integration for changing type systems.
R. D. Falgout, T. A. Manteuffel, B. O'Neill, and J. B. Schroder,
Multigrid reduction in time with Richardson extrapolation.
S. C. Brenner, J. C. Garay, and L.-y. Sung, Additive Schwarz
preconditioners for a localized orthogonal decomposition method.
R. Ramlau and B. Stadler, An augmented wavelet reconstructor for
atmospheric tomography.
H. Majidian, Modified Filon-Clenshaw-Curtis rules for oscillatory
integrals with a nonlinear oscillator.
K. Dunn, R. Lui, and M. Sarkis, An unconditionally stable
semi-implicit CutFEM for an interaction problem between an elastic
membrane and an incompressible fluid.
T. Hrycak and S. Schmutzhard, Error bounds for the numerical
evaluation of Legendre polynomials by a three-term recurrence.
L. Fermo and C. van der Mee, Volterra integral equations with highly
oscillatory kernels: a new numerical method with applications.
M. Reichelt, M. Windisch, G. Offner, and S. Santner, A multigrid
method for elasto-hydrodynamic contact simulations of radial slider
bearing.
M. Manguoglu and V. Mehrmann, A two-level iterative scheme for general
sparse linear systems based on approximate skew-symmetrizers.
M. Stoll and M. Winkler, Optimal Dirichlet control of partial
differential equations on networks.
V. Noferini, L. Robol, and R. Vandebril, Structured backward errors in
linearizations.
D. Occorsio and M. Grazia Russo, A mixed collocation scheme for
solving second kind Fredholm integral equations in [-1,1].
H. Hakula, S. Nasyrov, and M. Vuorinen, Conformal moduli of symmetric
circular quadrilaterals with cusps.
M. Hanke, Mathematical analysis of some iterative methods for the
reconstruction of memory kernels.
M. Mazza, S. Serra-Capizzano, and M. Usman, Symbol-based
preconditioning for Riesz distributed-order space-fractional diffusion
equations.
H. Gottschalk and K. Kahl, Coarsening in algebraic multigrid using
Gaussian processes.
L. Garcia Ramos, O. Sete, and R. Nabben, Preconditioning the Helmholtz
equation with the shifted Laplacian and Faber polynomials.
F. Tatsuoka, T. Sogabe, Y. Miyatake, T. Kemmochi, and S.-L. Zhang,
Computing the matrix fractional power with the double exponential
formula.
D. Cai and J. Xia, A stable matrix version of the fast multipole
method: stabilization strategies and examples.
S. Steinerberger, On the regularization effect of stochastic gradient
descent applied to least-squares.
From: Ali R. Soheili soheili@um.ac.ir
Date: October 12, 2021
Subject: Contents, Iranian J of Numerical Analysis and Optimization, 11 (2)
Iranian Journal of Numerical Analysis and Optimization Volume 11,
Issue 2 - Serial Number 20, Summer and Autumn 2021, Pages 235-511
https://ijnao.um.ac.ir/issue_2995_5166.html
Contents
Trainable fourth-order partial differential equations for image noise
removal, N. Khoeiniha, S.M. Hosseini and R. Davoudi
Exponentially fitted tension spline method for singularly perturbed
differential difference equations, M.M. Woldaregay, and G.F. Duressa
New class of hybrid explicit methods for numerical solution of optimal
control problems, M. Ebadi, I. Malih Maleki, and A. Ebadian
The strict complementarity in linear fractional optimization, M.
Mehdiloo, K. Tone and M.B. Ahmadi
Solving quantum optimal control problems by wavelets method, M.
Rahimi, S. M.Karbassi and M.R. Hooshmandasl
Singularly perturbed robin type boundary value problems with
discontinuous source term in geophysical fluid dynamics, B.M.
Abagero, G.F. Duressa and H.G. Debela
Two new approximations to Caputo-Fabrizio fractional equation on
non-uniform meshes and its applications, Z. Soori and A. Aminataei
Application of Newton-Cotes quadrature rule for nonlinear Hammerstein
integral equations, A. Shahsavaran
Investigating a claim about resource complexity measure, H.R.
Yousefzadeh
A new algorithm for solving linear programming problems with bipolar
fuzzy relation equation constraints, S. Aliannezhadi and A. Abbasi
Molai
Review of the strain-based formulation for analysis of plane
structures, Part I: Formulation of basics and the existing elements,
M. Rezaiee-Pajand, N. Gharaei-Moghaddam, and M. Ramezani
Review of the strain-based formulation for analysis of plane
structures, Part II: Evaluation of the numerical performance, M.
Rezaiee-Pajand, N. Gharaei-Moghaddam, and M. Ramezani
The Iranian Journal of Numerical Analysis and Optimization (IJNAO)
publishes original papers of high scientific value in all areas of
numerical analysis and optimization. IJNAO is an open-access journal
and all contributions to IJNAO are published free of charge and there
is no article submission charge. The Iranian Journal of Numerical
Analysis and Optimization is indexed in Scopus, zbMATH, DOAJ, and
COPE. For more information, please visit: https://ijnao.um.ac.ir/
From: Claude Brezinski claude.brezinski@univ-lille.fr
Date: October 08, 2021
Subject: Contents, Numerical Algorithms, 88 (3)
Table of Contents
Numerical Algorithms, Vol. 88, No. 3
The FMM accelerated PIES with the modified binary tree in solving
potential problems for the domains with curvilinear boundaries,
Andrzej Kuzelewski, Eugeniusz Zieniuk
Extrapolated sequential constraint method for variational inequality
over the intersection of fixed-point sets, Mootta Prangprakhon, Nimit
Nimana
Highly efficient schemes for time-fractional Allen-Cahn equation using
extended SAV approach, Dianming Hou, Hongyi Zhu, Chuanju Xu
A first-order inexact primal-dual algorithm for a class of
convex-concave saddle point problems, Fan Jiang, Zhongming Wu, Xingju
Cai, Hongchao Zhang
A second-order decoupled algorithm with different subdomain time steps
for the non-stationary Stokes/Darcy model, Dandan Xue, Yanren Hou
Blossoming and Hermite-Pade approximation for hypergeometric series,
Rachid Ait-Haddou, Marie-Laurence Mazure
A representation of the interpolation polynomial, Mircea Ivan, Vicuta
Neagos
Orthogonal polynomials relative to a generalized Marchenko-Pastur
probability measure, Walter Gautschi, Gradimir V. Milovanovic
A neurodynamic approach to zero-one quadratic programming, Yigui Ou,
Haichan Lin
Regularization of inverse problems by an approximate matrix-function
technique, Stefano Cipolla, Marco Donatelli, Fabio Durastante
On the preserving of the maximum principle and energy stability of
high-order implicit-explicit Runge-Kutta schemes for the
space-fractional Allen-Cahn equation, Hong Zhang, Jingye Yan, Xu Qian,
Xianming Gu, Songhe Song
Accurate error estimation in CG, Gerard Meurant, Jan Papez, Petr Tichy
Weak Galerkin finite element methods with or without stabilizers,
Xiaoshen Wang, Xiu Ye, Shangyou Zhang
On the convergence of Krylov methods with low-rank truncations, Davide
Palitta, Patrick Kuerschner
Inertial methods for finding minimum-norm solutions of the split
variational inequality problem beyond monotonicity, G. N. Ogwo,
C. Izuchukwu, O. T. Mewomo
A fast Fourier-Galerkin method solving boundary integral equations for
the Helmholtz equation with exponential convergence, Ying Jiang, Bo
Wang, Dandan Yu
Efficient quadrature rules for the singularly oscillatory Bessel
transforms and their error analysis, Hongchao Kang, Chunzhi Xiang,
Zhenhua Xu, Hong Wang
Multilevel augmentation methods for eigen-problems of compact integral
operators, Guangqing Long, Rong Jie, Li-bin Liu
End of Digest
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